Study on the Fatigue Bending Strength of Cylindrical Components Manufactured by External WAAM

This study investigates the fatigue bending strength, measured as the Mean of Fatigue Cycles (N), of cylindrical components produced by external wire arc additive manufacturing (WAAM) through a Taguchi L25 orthogonal array and linear regression analysis. Five welding parameters-welding current (Ampe), offset distance (mm), step length (mm), welding speed (mm/min), and specimen gauge diameter (mm)-were evaluated to maximize N using signal-to-noise (S/N) ratios. Nominal bending stresses (σ) ranged from 45 to 54 MPa, ANOVA on raw replicate data (25 runs, 3 replicates) confirmed specimen gauge diameter = 17 mm and weld current = 125 A as dominant, with F = 171.62 (p < 0.001, eta² = 0.62 [95% confidence intervals (CI) 0.55-0.68]) for specimen gauge diameter and F = 6.13 (p < 0.001, eta² = 0.13 [95% CI 0.08-0.18]) for weld current, accounting for ~75% of the variance. Optimal settings (offset distance = 3.0 mm, step length = 1000 mm, welding speed = 550 mm/min, specimen gauge diameter = 17 mm) achieved S/N = 111.35 dB, predicting N ≈ 350,000-380,000 cycles, a 22-33% improvement. Interactions between specimen gauge diameter and speed, and between weld current and offset distance, suggested enhanced strength at speed = 400-450 mm/min for specimen gauge diameter = 17 mm. Basquin's law (b ≈ 0.72, R² = 0.992) confirmed weld current as key. The linear regression model (adjusted R² = 0.9506) had coefficients for specimen gauge diameter (+70,120 cycles/mm, p < 0.001) and weld current (+1088 cycles/Ampe, p = 0.02), but lower test R² = 0.7212 via cross-validation (60/20/20 split) indicates overfitting due to small dataset size (25 runs), suggesting larger datasets or nonlinear models (e.g., polynomial regression, RSM). Confirmation runs (N = 317,082, 95% CI [287,000-347,000]) validated the results within ~13% error. WAAM reaches 80-90% of traditional manufacturing (TM) fatigue performance, with a 10-20% gap due to the microstructure; recommendations include post-treatments and safety factors (~1.2).